Results 161 to 170 of about 453,994 (310)
Auto-arrange buildings in urban planning with DQN. [PDF]
Lin P, Shi G, Hu C, Zhang J, Huang Y.
europepmc +1 more source
Abstract Wellbeing in higher education (HE) in the United Kingdom has been increasingly prioritised for many institutions, with a growing demand for student support requests. There are various determinants in life that can influence mental health. As such, protected characteristics, including race, can indicate that students who are Black or Asian ...
Amy Bywater, Helen Keane
wiley +1 more source
A unified deep learning framework integrating OpenStreetMap for multi-domain urban planning tasks. [PDF]
Chen Y, Afandi WS, Gura D, Kosenok Y.
europepmc +1 more source
Biomimetic method of emergency life channel urban planning in Wuhan using slime mold networks. [PDF]
Tan G, Wang Y, Cao X, Xu L.
europepmc +1 more source
Abstract Young people in the United States (and beyond) access spaces for activism in varied ways, including the out‐of‐school time sector, where youth activism (YA) groups draw on informal learning pedagogies to engage young people in collective action.
Laura Weiner
wiley +1 more source
This article presents the thesis abstracts of Bánszky Botond, Eszlári Gábor Tamás, Fejér Napsugár Anna, Jávor Ádám, Keller Réka, Klenczner Tamás Áron, Koncz Bianka Amaril, Kuna Máté, Limbach Noémi Anna, Lipcsei Dániel, Pellet Dávid Philippe, Pizmány ...
Botond Bánszky +17 more
doaj
A review of urban planning tools for empowering public participation. [PDF]
Hanan S, Carhart N.
europepmc +1 more source
Abstract This study examined teachers' perspectives on how children benefit from time in nature, how disadvantage shapes access and the role of schools in facilitating such access. Drawing on interviews conducted in 2022 with 25 UK primary school teachers who participated in Generation Wild, a nature connection programme for schools in economically ...
Nicola Parkin +6 more
wiley +1 more source
Decoding green space supply-demand mismatch through urban morphology: Toward equitable urban planning with explainable machine learning. [PDF]
Sun L, Liu W, Liu Q.
europepmc +1 more source

